ArticleAsian bioethics review2024
The Environmental Costs of Artificial Intelligence for Healthcare.
Article in Asian bioethics review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Concerns of Using Large Language Models in Health Care Research and Practice: Umbrella Review.Journal of medical Internet research · 2026Pooled it
- The Incarnate Clinic: Pope Leo XIV's Magnifica Humanitas, AI Optimization, and the Bioethics of Technological Colonialism in Philippine Healthcare.Journal of religion and health · 2026Article
- Perspective: Machine Learning for Health Should Consider Social Drivers of Health.Proceedings of machine learning research · 2026Article
- Tracking the Evolving Role of Artificial Intelligence in Implementation Science: Protocol for a Living Scoping Review of Applications, Evaluation Approaches and Outcomes.F1000Research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Healthcare has emerged as a key setting where expectations are rising for the potential benefits of artificial intelligence (AI), encompassing a range of technologies of varying utility and benefit. This paper argues that, even as the development of AI for healthcare has been pushed forward by a range of public and private actors, insufficient attention has been paid to a key contradiction at the center of AI for healthcare: that its pursuit to improve health is necessarily accompanied by environmental costs which pose risks to human and environmental health-costs which are not necessarily directly borne by those benefiting from the technologies. This perspective paper begins by examining the purported promise of AI in healthcare, contrasting this with the environmental costs which arise across the AI lifecycle, to highlight this contradiction inherent in the pursuit of AI. Its advancement-including in healthcare-is often described through deterministic language that presents it as inevitable. Yet, this paper argues that there is need for recognition of the environmental harm which this pursuit can lead to. Given recent initiatives to incorporate stakeholder involvement into decision-making around AI, the paper closes with a call for an expanded conception of stakeholders in AI for healthcare, to include consideration of those who may be indirectly affected by its development and deployment.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.